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What would you build if you could run reinforcement learning (RL) post-training on a 32B LLM (on a single H100) in 4-bit NVFP4 with BF16-level accuracy and 1.2–1.5× step speedup? NVIDIA researchers (with collaborators...

In this tutorial, we’ll explore how to build a context-collapsed LLM agent that efficiently solves long-term, complex tasks by intelligently managing limited context. We design agents to break large tasks into smaller subtasks, perform...

Anthropic release Claude Haiku 4.5a latency-optimized “small” model that can provide Encoding performance levels similar to Claude Sonnet 4 while running More than twice the speed, one-third less cost. The model is immediately available...

How would your agent stack change if a policy could be trained purely on its outcome-based deployment (no rewards, no demonstrations) but beat imitation learning on eight benchmarks? Yuan Super Intelligence Laboratory proposed “early...

Do you really need a huge VLM when a dense Qwen3-VL 4B/8B (instruction/think) with FP8 runs in low VRAM but retains 256K→1M context and full feature surface? Alibaba Qwen Team Expands its intermodal lineup...

Andrej Karpathy is open source nano chata compact, dependency-light codebase that implements the full ChatGPT-style stack (from tagger training to Web UI inference), designed for repeatable, hackable LLM training on a single multi-GPU node....

In this tutorial we will explore the following advanced features py testone of the most powerful testing frameworks in Python. We build a complete mini-project from scratch, demonstrating fixtures, markers, plugins, parameterization and custom...